1. Technical Field
The present invention relates to multiple-label data analysis.
2. Discussion of the Related Art
In data analysis, it is usually the case that data points are labeled by one labeler (e.g., an expert in the task/data domain), or they are not labeled at all. In general, data points can be any representation of information such as database records, image/text features, documents, biological sequences, etc. A great number of data analysis tasks have been proposed for these situations (e.g., most supervised and unsupervised machine learning algorithms). However, a much less explored area of data analysis involves labels that are provided by multiple labelers, including the case where certain labelers only label some or different data points. Accordingly, there exists a need for providing a data analysis formulation for this situation.